Computational Methods in Psychiatry

Computational Methods in Psychiatry

This book presents a particular area of interest in computing psychiatry with the modelling of mood and anxiety disorders. It highlights various methods for building these models. Clinical applications are prevalent due to the growth and interaction of these multiple approaches. Besides, it outlines some original predictive and computational modelling ideas for enhancing psychological treatment interventions. Computational psychiatry combines multiple levels and types of computation with different data types to improve mental illness understanding, prediction, and treatment. This book presents a particular area of interest in computing psychiatry with the modelling of mood and anxiety disorders. It highlights various methods for building these models. Clinical applications are prevalent due to the growth and interaction of these multiple approaches. Besides, it outlines some original predictive and computational modelling ideas for enhancing psychological treatment interventions. Computational psychiatry combines multiple levels and types of computation with different data types to improve mental illness understanding, prediction, and treatment. Dr Gopi Battineni is a research associate at the Clinical research centre, School of Medicinal and Health Products Sciences, University of Camerino, Italy since 2022. A master’s degree (with honours) in Computer Science and Engineering from Sheffield Hallam University, UK in 2016; and a master’s degree (with honours) in Enterprise Engineering from the University of Bordeaux, France in 2018, and a PhD in One health at the University of Camerino in 2021 with award of excellent cum lode. His research area includes telemedicine, process mining, natural language processing, data mining, big data, and machine learning. Dr Battineni is a member of the European Research Committee and has published more than 90 research papers in SCI, SCIE and Scopus-indexed journals and attending conferences, seminars, and guest talks on an international platform. He is a reviewer of many reputed international journals from different popular publishing houses such as Elsevier, MDPI, Wiley, Dove, plus one, BMJ etc. He managed and chaired different international conferences. He is an Associate Editor with reputed SCIE Indexed journals: Journal of Personalized Medicine and Algorithms (MDPI, Switzerland). Dr Mamta Mittal is working as Head and Associate Professor (Data Analytics and Data Science) at Delhi Skill & Entrepreneurship University (under the Government of NCT Delhi), New Delhi. She received PhD in Computer Science and Engineering from Thapar University, Patiala. She has been teaching for the last 18+ years with an emphasis on Data Mining, Machine Learning, DBMS, and Data Structure. Dr Mittal is a Lifetime member of CSI and published and communicated more than 90 research papers in SCI, SCIE, and Scopus indexed Journals. She holds five patents and two copyrights in Artificial Intelligence, IoT, and Deep Learning. Dr Mittal has edited/authored many books with reputed publishers like Springer, IOS Press, Elsevier, and CRC Press and working on DST approved Project “Development of IoT-based hybrid navigation module for mid-sized autonomous vehicles” with a research grant of 25 Lakhs. Currently, she is guiding PhD scholars in Machine Learning, Computer Vision, and Deep Learning. She is the book Series editor of Health Informatics & Healthcare: using AI & Smart Computing & another Series Edge AI in Future Computing with CRC Press, Taylor & Francis, USA. Dr Mittal is an Editorial Board member with InterScience, Bentham Science, Springer, and Elsevier and has Chaired several Conferences. She is Associate Editor with reputed SCIE Indexed journals: Earth Information Science (Springer) and Dyna (Spain). Dr Nalini Chintalapudi is a researcher at the clinical research centre, School of Medicinal and Health Products Sciences, University of Camerino in Italy. She earned a degree (with first-class distinction) in Computer Science at Jawaharlal Nehru Technological University, India; a master’s degree (with honours) in Computer Science and Engineering from the same university in 2015. She completed PhD in Computer Science and Mathematics at the University of Camerino. Her research area includes Text mining, Natural Language Processing, Data mining, big data and Machine learning. Dr Nalini Chintalapudi is a member of the European Research Committee and has published more than 45 research papers in SCI, SCIE and Scopus-indexed journals.